Image of PERBANDINGAN METODE MULTI OBJECTIVE OPTIMIZATION ON THE BASIS OF RATIO ANALYSIS DAN SIMPLE ADDITIVE WEIGHTING DALAM PEMILIHAN BIJI KOPI ARABIKA TERBAIK

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PERBANDINGAN METODE MULTI OBJECTIVE OPTIMIZATION ON THE BASIS OF RATIO ANALYSIS DAN SIMPLE ADDITIVE WEIGHTING DALAM PEMILIHAN BIJI KOPI ARABIKA TERBAIK

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Arabica coffee beans are the most widely consumed raw material for coffee beverages. Arabica coffee beans have a higher market price than other types of coffee beans because of their high quality.In making a decision to choose the best arabica coffee beans, a system is needed, namely Decision Support System. This research to obtain information about the best Arabica coffee beans using the Multi Objective Optimization on the basis of Ratio Analysis (MOORA) and Simple Additive Weighting (SAW) methods. Arabica coffe beans in this research consisted of 25 types, namely Java Ijen Honey, Kayu Aro Natural, Puntang Honey, Java Ijen Natural, Gunung Malabar Natural, Pantan Musara Honey, Gapura Washed Dry Hull, Toraja Full Washed, Kintamani Natural, Tao Toba Natural, Nusa Bunga Semi Washed, Benteng Alla Full Washed, Malabar Natural, Flores Honey, Gayo Avatara Natural, Crazy Fruit Natural, Weja Kanon Natural, Kerinci Natural, Manggarai Uwu Natural, Toraja Sapan Semi Washed, Flores Natural, Kerinci Full Washed, Lintong Honey, Aceh Gayo Wet Hull, and Solok Honey. Based on the results and interpretation, it can be concluded that the MOORA and SAW methods produce Gayo Avatara Natural as the best alternative, followed by Aceh Gayo Wet Hull, Java Natural Hull and Java Honey Honey. This research recommends the MOORA and SAW methods as decision support.

Availability
Inventory Code Barcode Call Number Location Status
2407003625T145188T1451882024Central Library (References)Available but not for loan - Not for Loan
Detail Information
Series Title
-
Call Number
T1451882024
Publisher
Indralaya : Prodi Ilmu Matematika, Fakultas Matematika dan Ilmu Pengetahuan Alam.,
Collation
xi, 31 hlm.; ilus.; 29 cm
Language
Indonesia
ISBN/ISSN
-
Classification
510.07
Content Type
Text
Media Type
unmediated
Carrier Type
-
Edition
-
Subject(s)
Prodi Ilmu Matematika
Biji Kopi Arabika
Specific Detail Info
-
Statement of Responsibility
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No other version available

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